Triple
T12587421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheikhpura |
E300503
|
entity |
| Predicate | hasRegionalLanguage |
P2982
|
FINISHED |
| Object | Angika |
E693546
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Angika | Statement: [Sheikhpura, hasRegionalLanguage, Angika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angika Context triple: [Sheikhpura, hasRegionalLanguage, Angika]
-
A.
Angika
chosen
Angika is an Eastern Indo-Aryan language spoken primarily in parts of Bihar and neighboring regions of India.
-
B.
Aruna
Aruna is a feminine given name most notably borne by Indian independence activist and political leader Aruna Asaf Ali.
-
C.
Aruna
Aruna is a figure in Hindu mythology known as the personified dawn and the divine charioteer who drives the sun god Surya across the sky.
-
D.
Arambala
Arambala is a small municipality in northeastern El Salvador known for its rural setting and location within the mountainous Morazán region.
-
E.
Nabaneeta
Nabaneeta is a feminine given name most notably borne by the acclaimed Indian Bengali writer and academic Nabaneeta Dev Sen.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954bbe72c8190aa11090bb6b480c9 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ebed164819083fbdaa775a59cd4 |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 9, 2026, 5:05 p.m.